Available online at www.worldscientificnews.com WSN 95 (2018) 224-234 EISSN 2392-2192 3D Mapping by Photogrammetry and LiDAR in Forest Studies Firoz Ahmad1,*, Md Meraj Uddin2, Laxmi Goparaju1 1Vindhyan Ecology and Natural History Foundation, Mirzapur, Uttar Pradesh, India 2Department of Mathematics, Ranchi University, Ranchi, Jharkhand, India E-mail address: [email protected] ABSTRACT Aerial imagery have long been used for forest Inventories due to the high correlation between tree height and forest biophysical properties to determine the vertical canopy structure which is an important variable in forest inventories. The development in photogrammetric softwares and large availability of aerial imagery has carved the path in 3D mapping and has accelerated significantly the use of photogrammetry in forest inventory. There is tremendous capacity of 3D mapping which has been recognized in research, development and management of forest ecosystem. The aim of this article is to provide insights of 3D mapping (photogrammetry including Lidar) in forest-related disciplines. We utilizing the satellite stereo pair and LiDAR point cloud as a case study for producing the anaglyph map and Canopy Height Model (CHM) respectively. The study also revealed the area verses canopy height graph. Present study has some strength because it was demonstrated the use of advance software module of ARC/GIS and Erdas Imagine for 3D mapping using Photogrammetry and LiDAR data sets which is highly useful in forest management, planning and decision making. Keywords: Stereo-Image, Photogrammetry, Lidar, Point cloud, Anaglyph, Canopy Height Model 1. INTRODUCTION The prime objective of forest mapping is to generate, manipulate and update various thematic datasets representing forestry attributes. These maps can be generated and utilized in forestry disciplines in forest research and education for forest management. Quantitative ( Received 27 February 2018; Accepted 13 March 2018; Date of Publication 14 March 2018 ) World Scientific News 95 (2018) 224-234 estimates of certain forest inventory attributes, such as mean tree height/ canopy height models (CHM) or timber volume, biomass, are crucial for sustainable forest management plan. Photogrammetry is the “art, science and technology of obtaining reliable information about physical objects and the environment through the process of recording, measuring and interpreting photographic images and patterns of electromagnetic radiant imagery and other phenomena” (American Society of Photogrammetry 1980). Photogrammetry can be used to obtain the information from hardcopy photographs or images. Sometimes the process of measuring information from photography and satellite imagery is known as metric photogrammetry. Interpreting information such as identifying and discriminating between various tree types from photography and imagery is known as interpretative photogrammetry (Wolf 1983). Satellite photogrammetry has little bit different compared to photogrammetric applications associated with aerial frame cameras because they utilize the sensor consisting of Charge-coupled device (CCD). A stereo satellite scene is obtained when two images of the same area are acquired on from different perspectives. The main advantages of digital photogrammetry in forestry 1) Digital photogrammetry includes various modules for image processing can execute various photogrammetry process (triangulation, orientation, orthoprojection) are fully automated whereas it facilitate stereoscopic measurement. 2) Digital automatic aero-triangulation facilitate the orientation of blocks of photos using least ground control points (GCPs) 3) After generation of stereo models it can be used for 3D-digitigition of various themes are significant for forest application and can be combined with various ancillary datasets. Few decade before, much information was generated by the photogrammetric evaluation of aerial photos by visual interpretation widely used in forestry application (Taniguchi 1961). Subsequently, 3D information of forest canopy was extracted using photogrammetric techniques (Korpela 2004) using analogue stereo-plotters and the measurement of tree heights were executed from image stereo-pairs (Baltsavias 1999) manually. Digital photogrammetry provides highly accurate output and subsequently economical, which overall reduces the price of the final products. Much photogrammetric software have been developed subsequently and provided the huge opportunity to generate 3D information from any kind of overlapping imagery. The Digital photogrammetric software began to be developed in the late 1980’s - early 1990’s (Lohmann et al. 1989, Leberl 1994, Baltsavias 1999). The advancement of high resolution satellite stereo pair imageries such as Spot, IKONOS, WorldView-2 and GeoEye2 stereo pair has greatly facilitated the analysis of 3D mapping up to the scale 1:5000 with enhanced image quality. The advent of digital imagery authorizes the automation of photogrammetric workflows to the concept of the point cloud. Although airborne laser scanning (ALS) data have many advantages (e.g. direct measurement of height, penetration of vegetation), aerial imagery still represents an essential data source for forest inventory. Therefore, nowadays aerial imageries are acquired frequently for vast areas for orthophoto production in developed countries. Photogrammetry and LiDAR could provide comprehensive spatial structure and tree species of forest, and have incomparable advantages in the long-time monitoring of forest -225- World Scientific News 95 (2018) 224-234 environment at individual tree or stand scale (Liu et al. 2017). A general flow diagram of photogrammetry/ LiDAR for forestry application is given in Figure 1. Figure 1. A general flow diagram of photogrammetry/LiDAR for forestry application. One more emerging 3D mapping technology is Light Detection and Ranging (LiDAR) – applied science can produce the distance measurements based on the return time of emitted light. LiDAR systems mounted on aircraft can be a cost-effective means to obtain three- dimensional (3D) information on forest attributes for diversified geographical areas with very high spatial resolution and unprecedented accuracy (Behera & Roy 2002). Such information is potentially more practical for forest inventories than the information from other remote sensing techniques (Lefsky et al. 2001; Coops et al. 2004; Maltamo et al. 2006). The new terminology UAV photogrammetry describes a photogrammetric measurement platform, which maneuvers remotely and is equipped with a photogrammetric measurement system, including, but not limited to a small or medium size still- camera, thermal or infrared camera systems, and airborne LiDAR system. Finally we can conclude the continuous progress and improvement in remote sensing data/ methodology/ software/ algorithms carved the path for forestry applications can be harnessed in large area at national level due to digital cameras to far visibility mapping range up to near infrared and thermal range and can be integrated into common working -226- World Scientific News 95 (2018) 224-234 environments for efficient analysis in 3-D (Ginzler & Waser 2017). The modeling of image- generated 3D- digital surface models (DSM) utilizes high-resolution aerial images with stereo pair coverage (Hirschmugl 2008, Leberl et al. 2010, Liang et al. 2016). Stereo photogrammetry is a type of the measurement of its three-dimensional position relative to a reference datum when any feature is scanned/imaged from two different perspectives. The use of digital aerial cameras which captured the image in digital format with an overlap images that are obtained for forest related inventory and monitoring. The progress in technology from film in early ages -to-digital format (CCD chip) has magnified by improvements to the radiometric properties of the images. The technological progress in resolution (radiometric and spatial) improving the characterization of detailed structures thus provide high quality of DSMs which strengthens the forest related application. The image quality in term of information determined by digital image resolution is defined by the ground sampling distance (GSD) largely depends on flying height and the camera (instrument specifications) used. Flying height is an important determinant for forestry applications, resulting in GSDs (e.g., Hirschmugl 2008, Bohlin et al. 2012, Jarnstedt et al. 2012, Nurminen et al. 2013) thus decide the scale of mapping (Zihlavniket al. 2007) and accuracy (Balenovic et al. 2017). The Bohlin et al. 2015 utilized the aerial images of three seasons for deriving the canopy height models (CHM) in deciduous forest of Sweden. Nasi et al., 2015 conducted a study in an urban forest located in the South of Finland by utilizing photogrammetric and hyperspectral images and identified the tree suffering from infestation. They classified the trees into classes of healthy, infested and dead, with overall accuracy were 76% (Cohen’s kappa 0.60), and the results were very significant. Lehmann et al. (2015) investigated the utility of UAV-acquired VNIR images to provide reliable remote-sensing data for producing maps of pest infestation and dead oaks to support intervention decisions in the management of forests located in the northwest Germany by utilizing photogrammetry, GIS and Image processing software. Aicardi et al. (2016) utilized 8 years DSMs from the year 2008 to 2015 obtained from LiDAR and UAV digital images (2015) to detect changes in a secondary